STOCHASTIC OPTIMIZATIONSTOCHASTIC OPTIMIZATION
STOCHASTIC OPTIMIZATION
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STOCHASTIC OPTIMIZATION OF PARAMETERS AND CONTROL LAWS OF THE AIRCRAFT GAS-TURBINE ENGINES – A STEP TO A ROBUST DESIGN

ISIP 2001, Nagana, Japan, 2001.

This paper is devoted to the problem of complex engineering systems robust designing. As applied to the aircraft gas-turbine engines it presents the main theses of stochastic approach to the multimeasure optimization of parameters and control laws. This approach allows us to optimize the engines taking into account the technological deflections which occur in the process of manufacturing of engine’s components as well as engine’s control deflections.

In the paper an aircraft gas-turbine engine is being analyzed as a stochastic system, which has a great number of uncertainties. It is shown that the optimum criterion value and therefore the design quality, being obtained with the deterministic approach, are nothing but the maximum achievable effect, one ought to seek. The question needs to be discussed concerning the possibility of implementation of this maximum effect. First there is the problem of assurance of the stability of the obtained solution under possible deflections of optimized parameters. Such deflections inevitably take place in practice while implementing any engineering project, even if there are used the most perfect technology levels. Secondly it is hard to predict if one can influence either the property or the extent of solution stability, optimizing parameters and control laws of an object being researched.

In the real-life conditions the numerical values of these uncertainties are unknown, therefore the classic deterministic approach is not applicable for the search of the robust solution. However there is just enough practical experience of GTE production, which allows us to estimate the law of distribution of these uncertainties with acceptable accuracy. Within the presented approach we use the assumption that the distribution law is normal and its standard deviation is known.

In the paper there are considered several types of stochastic optimization criteria. They are the probability of assurance of the criterion value which is not worse than a pre-defined value; the mathematical expectation of the goal parameter value; the dispersion of the optimized parameter, and the complex probabilistic criterion, taking into account both dispersion and mathematical expectation. The comparative analysis of these criteria is presented.

This paper presents some results dealing with the search of optimum control laws of mixed flow turbofan engine for throttle operating modes. These optimization problems have been aimed at the minimization of the specific fuel consumption over the range of engine throttle thrust under pre-defined flight conditions. The researches have been carried out using the mathematical model of the engine with 2-D axial symmetrical simulation of the low pressure compressor. The dispersions in the control laws implementation have been taken into account, i.e. we have treated the probabilistic character of obtained control laws.

These optimization problems have been successfully solved, and according to their result it has been proved that it is hard to implement in practice the deterministic solution. However the results which have been obtained using the stochastic criteria have much better robustness than that of the deterministic problems. The physical nature of the solution robust features improvement is discussed in the paper.


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